The AI red team service exposes hidden safety and security threats across the entire lifecycle of artificial intelligence (AI) systems by applying an adversarial mindset to assess AI systems during design, development, deployment, and operations stages.

LLM Vulnerability Scanner and Guardrails provides comprehensive assessment of LLM vulnerabilities and automatic application of optimal defensive techniques to generative AI on LLMs.

The Einstein Trust Layer is a secure AI architecture built into the Salesforce platform that provides guardrails to protect data privacy and security, improve the safety and accuracy of AI outputs, and enable Salesforce customers to use generative AI responsibly within Salesforce applications.

The OWASP Top 10 for Large Language Model (LLM) Applications is a written guidance document developed by the OWASP community to identify the most critical security risks affecting applications that use large language models.

garak is an open-source LLM vulnerability scanner developed by NVIDIA that probes large language models for security weaknesses including prompt injection, jailbreaks, hallucination, toxicity, data leakage, and misinformation.

ASQI Engineer is an open-source framework for testing and assuring AI systems. Built for scale and reliability, it uses containerised test packages, automated assessments, and repeatable workflows to make evaluation transparent and robust. With ASQI Engineer, organisations also run ASQIs that they have created themselves, giving teams full control and confidence in AI quality.

ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally accessible, living knowledge base of adversary tactics and techniques against Al-enabled systems based on real-world attack observations and realistic demonstrations from Al red teams and security groups.

HiddenLayer’s AISec Platform is a GenAI Protection Suite purpose-built to ensure the integrity of AI models throughout the MLOps pipeline. The platform provides detection and response for GenAI and traditional AI models to detect prompt injections, adversarial AI attacks, and digital supply chain vulnerabilities.

ISO/IEC 25023:2016 defines quality measures for quantitatively evaluating system and software product quality in terms of characteristics and subcharacteristics defined in ISO/IEC 25010 and is intended to be used together with ISO/IEC 25010.

Continuous automated red teaming for AI, minimize security threats to AI models and applications.

garak, Generative AI Red-teaming & Assessment Kit, is an LLM vulnerability scanner. Garak checks if an LLM can be made to fail.

AI Security Platform for GenAI and Conversational AI applications. Probe enables security officers and developers identify, mitigate, and monitor AI system security.

This Recommendation specifies an architectural framework for network automation based on artificial intelligence (AI) for resource and fault management in future networks, including international mobile telecommunications-2020 (IMT-2020).

This Recommendation provides an architectural framework for machine learning (ML) models serving in future networks including IMT-2020, i.

This Recommendation provides system context, functional requirements and use cases for machine learning as a service (MLaaS).

PAS 11281 is the international standard on road vehicles that gives recommendations for managing security risks that might lead to a compromise of safety in a connected automotive ecosystem.

Methodology extending current experiences on the characteristics of 'adaptive networks' such as virtualization, self-organization, self-configuration, self-optimization, self-healing and self-learning offer huge advantages in future networks.

Effective data management and operation is extremely important. This work item is purposed to draft a GR of data operation requirements and mechanisms to better serve ENI system.

This Recommendation provides a framework for artificial intelligence (AI) enhanced telecom operation and management (AITOM).

This Recommendation specifies a functional framework for network service provisioning based on artificial intelligence (AI) in future networks, including international mobile telecommunication-2020 (IMT-2020).